Knowledge-Based Systems in Agriculture and Natural Resource Management
Stone, Nicholas D., Engel, Bernard A.
The second workshop in two years on the integration of knowledge-based systems with conventional computer techniques in agriculture and natural resource management (NRM) was held 18-19 August 1989 in Detroit, Michigan, in conjunction with the Tenth International Joint Conference on Artificial Intelligence. The workshop drew scientists from the United States and Canada, working in disciplines from engineering to entomology in universities, government, and industry. Twenty-two papers were presented at the workshop, after which participants were asked to discuss several key questions about the development, delivery, and use of knowledge-based systems in solving problems in agriculture and NRM.
AAAI News
Thirty users of AI systems, 8. Make sure everyone knows at the Intelligence has announced that, key role in systems that enhance the 1. Integrating AI with traditional starting next year, its National Conference human values of the world we live in." He 2. AI may be only part of the system/ The 1991 AAAI Conferences will noted that, "Some of the most important solution, but it is increasingly the take place in Anaheim, California results of technology transfer part that makes the whole work. The National Conference will be the unexpected." "This is a recognition of changing significant benefits." "As AI moves more broadly champion" outside the AI/IS area, presentations focused on the approaches AI solutions that were only theory 12 to 18 months ago."
Future Directions in Natural Language Processing: The Bolt Beranek and Newman Natural Language Symposium
The Workshop on Future Directions in NLP was held at Bolt Beranek and Newman, Inc. (BBN), in Cambridge, Massachusetts, from 29 November to 1 December 1989. The workshop was organized and hosted by Madeleine Bates and Ralph Weischedel of the BBN Speech and Natural Language Department and sponsored by BBN's Science Development Program.
Technology, Work, and the Organization: The Impact of Expert Systems
This article examines the near-term impact of expert system technology on work and the organization. From this analysis, a framework is constructed for viewing the impact of these technologies -- and technologies in general -- as a function of the technology itself; market realities; and personal, organizational, and societal values and policy choices. Two scenarios are proposed with respect to the application of this framework to expert systems. The second scenario posits that expert system diffusion will be pulled by, and will be a contributing factor toward, the evolution of the lean, flexible, knowledge-intensive, postindustrial organization.
Components of Expertise
It reviews existing approaches such as inference structures, the distinction between deep and surface knowledge, problem-solving methods, and generic tasks. A new synthesis is put forward in the form of a componential framework that stresses modularity and an analysis of the pragmatic constraints on the task. The analysis of a rule from an existing expert system (the Dipmeter Advisor) is used to illustrate the framework.
Components of Expertise
It (McDermott 1988), and the idea of generic also helps to explicitly focus on how to go tasks and task-specific architectures (Chandrasekaran from the knowledge level to the symbol or 1983). These various proposals are program level. I call this in-between level the obviously related to each other, which makes knowledge-use level. At the knowledge-use it desirable to construct a synthesis that combines level, we focus on issues such as how the their strengths. Such a synthesis is presented overall task will be decomposed into manageable here in the form of a componential subtasks, what ordering will be imposed framework. The framework stresses modularity on the tasks, what kind of access to knowledge and consideration of the pragmatic constraints will be needed (and, consequently, what of the domain.